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Sparse PDF Maps for Non-Linear Multi-Resolution Image Operations
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DOI：10.1145/2366145.2366152.png)
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Abstract
En 中文
We introduce a new type of multi-resolution image pyramid for high-resolution images called sparse pdf maps (sPDF-maps). Each pyramid level consists of a sparse encoding of continuous probability density functions (pdfs) of pixel neighborhoods in the original image. The encoded pdfs enable the accurate computation of non-linear image operations directly in any pyramid level with proper pre-filtering for anti-aliasing, without accessing higher or lower resolutions. The sparsity of sPDF-maps makes them feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters (e. g., median or mode filters), and bilateral filters.
Keywords:
image pyramids
mipmapping
anti-aliasing
multi-resolution filtering
display-aware filtering
smoothed local histogram filtering
bilateral filtering
local Laplacian filtering
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